Confidence statements for efficiency estimates from stochastic frontier models

This paper is an empirical study of the uncertainty associated with technical efficiency estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the very strong to the relatively weak. We demonstrate empirically how the degree of uncertainty associated with these estimates relates to the strength of the assumptions made and to various features of the data.     

Technical efficiency measures for dairy farms using panel data: A comparison of alternative model specifications

This article examines the impact of fixed effects production functions vis-à-vis stochastic production frontiers on technical efficiency measures. An unbalanced panel consisting of 96 Vermont dairy farmers for the 1971–1984 period was used in the analysis. The models examined incorporated both time-variant and time-invariant technical efficiency. The major source of variation in efficiency levels across models stemmed from the assumption made concerning the distribution of the one-sided term in the stochastic frontiers. In general, the fixed effects technique was found superior to the stochastic production frontier methodology. Despite the fact that the results of various statistical tests revealed the superiority of some specifications over others, the overall conclusion of the study is that the efficiency analysis was fairly consistent throughout all the models considered.     

Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming

This paper proposes an econometric framework for joint estimation of technology and technology choice/adoption decision. The procedure takes into account the endogeneity of technology choice, which is likely to depend on inefficiency. Similarly, output from each technology depends on inefficiency. The effect of the dual role of inefficiency is estimated using a single-step maximum likelihood method. The proposed model is applied to a sample of conventional and organic dairy farms in Finland. The main findings are: the conventional technology is more productive, ceteris paribus; organic farms are, on average, less efficient technically than conventional farms; both efficiency and subsidy are found to be driving forces behind adoption of organic technology.     

Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis

This paper analyses the regional technical efficiency of Chinese iron and steel industry from 1996 to 2010 by a network DEA procedure, and provides the smoothed bootstrap network DEA strategy for the sensitivity analysis of the efficiency measure to sampling variation of the estimated frontier. Furthermore, the evolution and convergence characteristics of regional technical efficiency are examined by a dynamic regression model based on different regional divisions of China. The empirical results show that there exist significant geographical differences in the technical efficiency of Chinese iron and steel industry. On the one hand, the technical efficiency of the eastern area, the central area and the western area is unbalanced, with a lower efficiency in the west and a higher one in the east. On the other hand, technical efficiency of Central Bohai, Yangtze River Delta and Pearl River Delta economic zones is higher than that of the other economic zones. In addition, the technical efficiency has a significant improvement during the period of the Eleventh Five-Year Plan. Following the convergence notation in economic growth theory, this paper also gives some convergence evidence of the technical efficiency towards the efficient frontier due to the catching-up effect. Finally, this paper explores the determinants of the technical efficiency, and discusses policy implications for Chinese iron and steel industry.     

Decomposition of cost efficiency and its application to Japanese-US electric utility comparisons

This paper presents a new formula for decomposing cost efficiency into technical, price, and allocative efficiencies in an environment marked by the fact that unit input prices differ among certain enterprises. We employed this formula in comparing cost efficiency between Japanese and US electric power companies, and found a significant difference in the price-based efficiency. However, negligible differences were found in the technical and allocative efficiencies.     

Consistent estimation of technical and allocative efficiencies for a semiparametric stochastic cost frontier with shadow input prices

Conventional parametric stochastic cost frontier models are likely to suffer from biased inferences due to misspecification and the ignorance of allocative efficiency (AE). To fill up the gap in the literature, this article proposes a semiparametric stochastic cost frontier with shadow input prices that combines a parametric portion with a nonparametric portion and that allows for the presence of both technical efficiency (TE) and AE. The introduction of AE and the nonparametric function into the cost function complicates substantially the estimation procedure. We develop a new estimation procedure that leads to consistent estimators and valid TE and AE measures, which are proved by conducting Monte Carlo simulations.     

Relationships between technical efficiency and subsidies for Czech farms: A two-stage robust approach

Subsidies for agriculture in the European Union have been a matter of debate for a long time. However, even after many years of debate, it remains unclear whether the subsidies have a positive or negative effect on farm efficiency. We propose a robust two-stage framework to study the subsidies-effect to farm technical efficiency while controlling farm heterogeneity. First, technical efficiency scores are computed using a modern robust data envelopment analysis model. Then, a quantile regression model is applied to explain the relationship between technical efficiency and the total subsidies and other commonly used explanatory variables. In the empirical part, we analyze a sample of Czech farms during the period from 2010 to 2015. It is revealed that the subsidies-effect is negative and varies based on the technical efficiency of the farm. Higher efficient farms face a less distorting effect than lower efficient farms.     

Evaluating cost efficiency and returns to scale in the Life Insurance Corporation of India using data envelopment analysis

This paper applies a new variant of data envelopment analysis model to examine the performance of Life Insurance Corporation (LIC) of India. The findings show a significant heterogeneity in the cost efficiency scores over the course of 19 years. A decline in performance after 1994-1995 can be taken as evidence of increasing allocative inefficiencies arising from the huge initial fixed cost undertaken by LIC in modernizing its operations. A significant increase in cost efficiency in 2000-2001 is, however, cause for optimism that LIC may now be realizing a benefit from such modernization. This will stand them in good stead in terms of future competition. Results from a sensitivity analysis are in broad agreement with the main findings of this study.     

Radial and nonradial measures of technical efficiency: An empirical illustration for Belgian local governments using an FDH reference technology

This paper serves two purposes. First, we argue that radial efficiency measures are inappropriate for the Free Disposal Hull (FDH) technology, and we provide a comparative analysis of alternative nonradial measures. In particular, using information on Belgian local government expenditures and output indicators we implement various radial and nonradial measures on the FDH reference technology, and we investigate to which extent these efficiency measures imply different distributions and rankings. Second, we analyze the patterns of measured technical efficiency implied by the various indices. Specifically, we investigate whether different measures make any substantial difference for the explanation of the calculated inefficiencies. The empirical results suggest that more important differences in rankings exist between radial and nonradial measures than between different nonradial alternatives; moreover, the radial and the nonradial efficiency measures do yield a somewhat different pattern of explanation.This is a revision of a paper presented at the 38th Conference of the Applied Econometrics Association in Athens (April 12–13, 1993). Comments of R. Goudriaan, Henry Tulkens, and two anonymous referees are gratefully acknowledged.     

Mafia risk perception: Evaluating the effect of organized crime on firm technical efficiency and investment proclivity

The presence of illegal organizations in economic development settings contributes to the Italian economy’s regional heterogeneity by exacerbating other inefficiencies. We aim to investigate how three indicators of awareness of criminal interest in a firm’s activities affect the latter’s efficiency, as well as examining a potential channel through which illegal activities could hinder firm performance, using a unique set of firm-level data. According to our findings, the presence of criminal network pressure in a firm’s environment reduces its technical efficiency and propensity to invest. This phenomenon is particularly strong in Italy’s underdeveloped regions, across all illicit considered and risk classes, with inefficiency doubling when the fear of crime becomes significant. A similar pattern emerges in terms of firm investment proclivity. The research findings are relevant for policymakers because they demonstrate that even the perception of a criminal threat has significant effects on a firm’s performance; consequently, enhancing legal protection could prevent significant economic and social costs.     

On the accuracy of bootstrap confidence intervals for efficiency levels in stochastic frontier models with panel data

We study the construction of confidence intervals for efficiency levels of individual firms in stochastic frontier models with panel data. The focus is on bootstrapping and related methods. We start with a survey of various versions of the bootstrap. We also propose a simple parametric alternative in which one acts as if the␣identity of the best firm is known. Monte Carlo simulations indicate that the parametric method works better than the␣percentile bootstrap, but not as well as bootstrap methods that make bias corrections. All of these methods are valid␣only for large time-series sample size (T), and correspondingly none of the methods yields very accurate confidence intervals except when T is large enough that the identity of the best firm is clear. We also present empirical results for two well-known data sets.      

Nonparametric estimation and testing of fixed effects panel data models

In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics.     

On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

Analysis of the behavior of technical inefficiency with respect to parameters and variables of a stochastic frontier model is a neglected area of research in frontier literature. An attempt in this direction, however, has recently been made. It has been shown that in a “standard” stochastic frontier model that both the firm level technical inefficiency and the production uncertainty are monotonically decreasing with observational error. In this paper we show, considering a stochastic frontier model whose error components are jointly distributed as truncated bivariate normal, that this property holds if and only if the distribution of observational error is negatively skewed. We also derive a necessary and sufficient condition under which both firm level technical inefficiency and production uncertainty are monotonically increasing with noise-inefficiency correlation. We next propose a new measure of the industry level production uncertainty and establish the necessary and sufficient condition for firm level technical inefficiency and production uncertainty to be monotonically increasing with industry level production uncertainty. We also study the limiting probabilistic behavior of these conditions under different parametric configuration of our model. Finally we carry out Monte Carlo simulations to study the sample behavior of the population monotonic property of the firm level technical inefficiency and production uncertainty in our model.

Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data

We show how the dynamic logit model for binary panel data may be approximated by a quadratic exponential model. Under the approximating model, simple sufficient statistics exist for the subject-specific parameters introduced to capture the unobserved heterogeneity between subjects. The latter must be distinguished from the state dependence which is accounted for by including the lagged response variable among the regressors. By conditioning on the sufficient statistics, we derive a pseudo conditional likelihood estimator of the structural parameters of the dynamic logit model, which is simple to compute. Asymptotic properties of this estimator are studied in detail. Simulation results show that the estimator is competitive in terms of efficiency with estimators recently proposed in the econometric literature.     

Shrinkage estimation of the exponentiated Weibull regression model for time-to-event data

The exponentiated Weibull distribution is a convenient alternative to the generalized gamma distribution to model time-to-event data. It accommodates both monotone and nonmonotone hazard shapes, and flexible enough to describe data with wide ranging characteristics. It can also be used for regression analysis of time-to-event data. The maximum likelihood method is thus far the most widely used technique for inference, though there is a considerable body of research of improving the maximum likelihood estimators in terms of asymptotic efficiency. For example, there has recently been considerable attention on applying James–Stein shrinkage ideas to parameter estimation in regression models. We propose nonpenalty shrinkage estimation for the exponentiated Weibull regression model for time-to-event data. Comparative studies suggest that the shrinkage estimators outperform the maximum likelihood estimators in terms of statistical efficiency. Overall, the shrinkage method leads to more accurate statistical inference, a fundamental and desirable component of statistical theory.     

The fundraising efficiency in U.S. non-profit art organizations: an application of a Bayesian estimation approach using the stochastic frontier production model

This article examines how efficient art organizations are in raising funds from private giving. We measure fundraising efficiency using a Bayesian estimation approach using the stochastic frontier production model. We show that fundraising efficiencies are generally quite low for art organizations in the U.S. when private giving is only considered as a fundraising output; however, when the effect of fundraising on ticket sales is considered, fundraising efficiencies improve substantially. We also show that government grants have a negative impact on fundraising efficiency and therefore partially crowd out private giving.     

Testing for heteroskedasticity and serial correlation in a random effects panel data model

This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as, a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests along with their likelihood ratio alternatives have good size and power under various forms of heteroskedasticity including exponential and quadratic functional forms.     

The impact of oil prices and the financial market on cost efficiency in the insurance and Takaful sectors: Evidence from a stochastic frontier analysis

The Gulf Cooperation Council’s (GCC) insurance industry, including conventional insurance and Takaful, has witnessed remarkable growth during the last decade. However, the economies of this region rely on oil as the primary stream of revenue and lack development in financial markets. This could affect the insurance industry. For this reason, this paper examines the impact of oil prices and the financial market on the cost efficiency of the insurance and Takaful sectors in GCC countries using a stochastic frontier cost function with data from 2009–2016. The results show that the relationship between oil prices and efficiency changes from positive to negative when the prices increase, whereas the relationship between the financial market and efficiency is negative. No clear evidence of the impact of oil prices on efficiency arises from the differences between conventional insurance and Takaful. However, there are differences regarding the financial market, with a negative impact on conventional insurance and a positive one on the Takaful business. The results of this study have implications for regulators and management. The Takaful industry is rapidly growing compared to conventional insurance in the GCC and, therefore, the financial market may have added benefits for the GCC region. However, caution is required in relation to the impact of the financial market on conventional insurance. Furthermore, management may require the development of strategies to deal with the nature of GCC economies to avoid shocks to oil prices.     

A collective labor supply model with complementarities in leisure: Identification and estimation by means of panel data

We present a novel identification strategy for a collective labor supply model that allows for complementarities in leisure (i.e., individuals may enjoy leisure more in company of their spouse). Individual preferences and the Pareto weights (which capture the intra-household bargaining process) are identified by making use of panel data with couples and individuals who became a widow(er) in the observation period, along with the assumption that an individual's preferences can only change in a particular manner after the spouse's death. The change in preferences comes from changes in observable variables that can be controlled for (like mental health) and from the loss of the possibility to jointly enjoy leisure after the couple's dissolution. We apply the model to American households coming from the first nine waves of the Health and Retirement Study (1992-2008) and show that complementarities in leisure are indeed important when modeling spouses' labor supply choices.     

Quasi-structural estimation of a model of childcare choices and child cognitive ability production

This article evaluates the effects of maternal vs. alternative care providers’ time inputs on children’s cognitive development using the sample of single mothers in the National Longitudinal Survey of Youth. To deal with the selection problem created by unobserved heterogeneity of mothers and children, we develop a model of mother’s employment and childcare decisions. We then obtain approximate decision rules for employment and childcare use, and estimate these jointly with the child’s cognitive ability production function. To help identify our selection model, we take advantage of the plausibly exogenous variation in employment and childcare choices of single mothers generated by the variation in welfare rules across states and over time created by the 1996 welfare reform legislation and earlier State waivers.